Factors Associated with Acute Malnutrition among Children Admitted to a Diarrhoea Treatment Facility in Bangladesh
Bibliographic record
Abstract
To assess the risk factors for acute malnutrition (weight-for-height z-score (WHZ) < -2), a case-control study was conducted during June-September 2012 in 449 children aged 6-59 months (178 with WHZ < -2 and 271 comparing children with WHZ ≥ -2 and no edema) admitted to the Dhaka Hospital of icddr,b in Bangladesh. The overall mean ± SD age was 12.0 ± 7.6 months, 38.5% (no difference between case and controls). The mean ± SD WHZ of cases and controls was -3.24 ± 1.01 versus -0.74 ± 0.95 (P < 0.001), respectively. Logistic regression analysis revealed that children with acute malnutrition were more likely than controls to be older (age > 1 year) (adjusted OR (AOR): 3.1, P = 0.004); have an undernourished mother (body mass index < 18.5), (AOR: 2.8, P = 0.017); have a father with no or a low-paying job (AOR: 5.8, P < 0.001); come from a family having a monthly income of <10,000 taka, (1 US$ = 80 taka) (AOR: 2.9, P = 0.008); and often have stopped predominant breastfeeding before 4 months of age (AOR: 2.7, P = 0.013). Improved understanding of these characteristics enables the design and targeting of preventive-intervention programs of childhood acute malnutrition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".